As is known in the art, materials are selected for use based on criteria including minimum strength requirements, useable life, and anticipated normal wear. Safety factors are typically factored into the design considerations to supplement material selection in order to aid in reducing the risk of failures including catastrophic failure. Failures occur when the required application strengths exceed the actual material strength either due to the misapplication of the material or due to material deterioration. During its useful life, material deteriorates and/or is weakened by external events such as mechanical and/or chemical actions arising from the type of application, repeated usage, hurricanes, earthquakes, storage, transportation, and the like; thus, raising safety, operational, functionality, and serviceability issues. The list of typical material includes, but is not limited to, aircraft, bridges, cranes, drilling rigs, frames, chemical plant components, engine components, oil country tubular goods (herein after referred to as “OCTG”), pipelines, power plant components, rails, refineries, rolling stoke, sea going vessels, service rigs, structures, vessels, workover rigs, other components of the above, combinations of the above, and similar items.
Material owners perform a remaining useful life (herein after referred to as “RUL”) estimation (herein after referred to as “RULE”) occasionally, often following a component failure. This RULE is mostly based on as-designed data occasionally supplemented by Non-Destructive Inspection (herein after referred to as “NDI”) data. Often, the absence of an NDI indication comprises the entire fitness for service assessment (herein after referred to as “FFS”) and RULE. NDI is typically carried out in order to verify that the material deterioration, from some of the known deterioration causes, has not reduced the material strength below the minimum application requirements.
Since its inception in the early 1900s, the NDI industry has utilized a variety of techniques and devices, alone or in combination with each other, with the majority based on the well known and well documented techniques of magnetic flux leakage (herein after referred to as “MFL”), eddy-current (herein after referred to as “EC”), magnetic particle, ultrasonic (herein after referred to as “UT”) radiation, such as x-ray and gamma ray, dye penetrant, and dimensional as well as visual and audible techniques. MFL and EC are also known as ElectroMagnetic Inspection (herein after referred to as “EMI”). Typical NDI devices deploy a single sensor per material area and are therefore classified as one-dimensional (herein after referred to as “1D”, “1D-NDI” and “1D-EMI”).
However, the limited data 1D-NDI provides for the Material-Under-Inspection (herein after referred to as “MUI”) does not adequately address the demanding material application RUL needs. After all, a century ago there was no drilling a 20,000 foot well in 10,000 feet of water in search for hydrocarbons or trains traveling at speeds in excess of 100 miles per hour or supersonic aircraft. For example, when 1D-NDI does not detect any corrosion pitting that exceeds its minimum detection capabilities, it is false to conclude that the material is fit for the application or its RUL satisfies the application needs. It is desirable therefore to provide Autonomous RULE (herein after referred to as “AutoRULE”) equipment and methods to the industry. AutoRULE must detect and recognize the “as-built” and/or “as-is” MUI features impacting its RULE including, but not limited to, imperfections.
The Distinction Between RULE Assessment and NDI
As carried out since its inception, NDI is examining the MUI for signals (flags) that exceed a preset threshold level while common MUI features, such as welds and couplings, typically saturate the NDI processing and they are ignored by the inspector, similar in appearance to elements 191A and 191B of FIG. 19B. Therefore, the end result of an NDI can be summarized as “within the limitations of the inspection technique(s), there were no material regions that gave rise to signals above the threshold level that were relevant according to the opinion of the inspector”. As will be discussed further, the combination of sensor signal filtering and threshold prior to any signal evaluations creates detection dead-zones, a standard NDI practice never the less. Such filter/threshold combination can be found throughout the patent record, such as in the 1931 U.S. Pat. No. 1,823,810 and the 2003 U.S. Pat. No. 6,594,591. Therefore, the absence of an NDI indication does not necessarily imply that the material is fit for service or meets the application RUL needs.
Another example of an NDI technique with different type detection dead-zones is Time of Flight Diffraction (herein after referred to as “TOFD”) of U.S. Pat. Nos. 6,904,818, 7,082,822, 7,104,125 used for the inspection of marine drilling risers. The near-surface TOFD dead zone is due to lateral waves and the far-surface TOFD dead zone is due to echoes. It should be noted that the major and minor axis surfaces of marine drilling risers experience the maximum vortex-induced-vibration (herein after referred to as “VIV”) loads and thus, cracking is expected to initiate at stress concentrators within the TOFD dead-zones, like the bottom of surface pits or the heat affected zone of welds. From actual fatigue and crack growth field runs, Stylwan has concluded that weld cracks tend to grow preferentially parallel to the surface (increase length) than into the wall (increase depth) and therefore would remain undetected by TOFD while undergoing their most rapid growth. The TOFD dead-zones are significant on used material, typically exceeding the maximum allowed imperfection depth. Therefore, the absence of a TOFD indication can be summarized as “there were no material regions with cracks deeper than the TOFD detection dead-zones” which by no means constitute a sound NDI on used material much less an FFS and/or a RULE.
On the other hand, RULE must examine and evaluate, as close as possible, 100% of the Material-Under-RUL-Assessment (herein after referred to as “MUA”) for 100% of features spanning from fatigue (2-D) all the way to wall thickness changes (A-WDS) and declare the MUA fit for continuing service and estimate its RUL only after all the features impact upon the MUA have been evaluated. It is well known that the presence of any imperfection alters the FFS of the MUA and impacts its RUL. Thus, it should be appreciated that the deployment of the AutoRULE would increase the overall safety and reliability as it would lead to MUA repair and/or replacement prior to a catastrophic failure as well as it will reduce and/or eliminate its premature replacement due to concerns when the conventional inspection periods are spaced far apart and/or when the conventional inspection provides an insignificant inspection coverage. In addition, it should be understood that material free of any imperfections may still not be fit for service in the particular application and/or deployment or it may have a shorter RUL.
There is a plethora of 1D-NDI systems in the patent record using terms such as, “Detect”, “Identify”, “Recognize” but only in the context that the sensor signal exceeds the preset threshold level and an indication is shown in the 1D-NDI readout device. The 1D-NDI readout device indication prompts the inspector to assign the material to the verification crew for further manual investigation. However, as shown further in FIGS. 2A and 2B, 1D-NDI cannot “connect or associate or know by some detail” the feature or even if the sensor signal is indeed associated with a feature; a task assigned entirely to the manual verification crew. As opposed to 1D-NDI, the present invention also uses terms such as, “Identify” and “Recognize” in the context of “connect or associate or know by some detail”. As shown further in FIGS. 2C and 2D, AutoRULE “knows by some detail” the imperfection and “connects and associates” the imperfection with known imperfection definitions. AutoRULE preferably uses FFS and RUL formulas and knowledge and is preferably able to export a file for use by a finite element analysis engine (herein after referred to as “FEA”) because AutoRULE “knows by some detail” the material features, as shown in FIGS. 3A through 3D. It should be understood that different FEA engines use different structure geometry import/export specifications.